Formulation of a decision support tool incorporating both genetic and non-genetic effects to rank young growing cattle on expected market value

Dairy Producers Who Market Their Surplus Progeny as Calves Use Germplasm With Slightly Lighter and Less-Conformed Carcasses Than Producers Who Rear Their Surplus Progeny Beyond Weaning

Understanding dairy producer mindset in service sire selection can provide useful information for different junctures along the commercial and extension animal breeding chain. It can aid the targeted marketing of bulls based on farm production systems but also provide useful information for delivering bespoke extension services. The objective of the present study was to examine if differences exist among dairy producers in their choice of dairy and beef service sires depending on the life stage at which the surplus progeny generated from such matings exit the dairy farm. This was predominantly based on evaluating the breed of beef sires used but also their genetic merit for calving difficulty and carcass traits, namely, carcass weight, conformation, and fat score; differences in genetic merit among dairy sires as well as among the dairy cows themselves were also considered. The objective was accomplished through the cross-sectional analyses of progeny fate data from 1,092,403 progeny born in 4,117 Irish dairy herds. Herd-years were categorized into one of four systems based on when the surplus progeny exited the dairy farm: (1) calves sold <70 days of age, (2) cattle sold as yearlings between 250 and 450 days of age, (3) prime cattle sold for finishing (slaughtered between 8 and 120 days of exiting the dairy farm), or (4) prime cattle sold for immediate slaughter (i.e., slaughtered within 7 days of exiting the dairy farm). The mean genetic merit of both the cows and service sires used across the four different systems was estimated using linear mixed models. Of the beef service sires used in herds that sold their surplus progeny as calves, their mean predicted transmitting ability for carcass weight and carcass conformation score was just 2.00 kg and 0.11 scores [scale of 1 (poor) to 15 (excellent)] inferior to the beef service sires used in herds that sold their surplus progeny as prime cattle for immediate slaughter. Similar trends, albeit of smaller magnitude, were evident when comparing the genetic merit of the dairy service sires used in those systems. Cows in herds that sold their surplus progeny as calves were genetically less likely to incur dystocia as well as to have lighter, less-conformed, and leaner carcasses than cows in herds that sold their surplus progeny post-weaning. Hence, results from the present study suggest that diversity in herd strategy regarding when surplus progeny exit the herd influences service sire selection choices in respect of genetic merit for dystocia and carcass attributes. That said, the biological difference based on the current pool of available service sires is small relative to the dairy producers that sell their surplus progeny as young calves; when expressed on a per standard deviation in genetic merit of the beef service sires used across all herds, the difference between extreme systems was, nonetheless, approximately half a standard deviation for carcass weight and conformation.

Predicting male dairy calf live weight for use in calf management decision support

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A robust yet simple statistical model for predicting young male dairy calf live weight was developed.

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The predictive model can be adapted to estimate the age when a calf reaches a target live weight.

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The model can be integrated into a decision support tool to inform calf labor and infrastructure management.

The growing awareness and scrutiny of the management of young dairy calves, especially male calves, necessitates a support tool to aid in the planning of resource allocation on dairy farms. There is a desire among some vendors for a minimum calf weight when purchasing young dairy bull calves. Hence, the objective of the present study was to investigate whether live weight of young calves (approximately 10–50 d old) can be predicted using readily accessible animal-level features, especially features that may be available in advance of birth. A multiple linear regression mixed model was developed with the live weight of 602 dairy bull calves aged between 10 and 42 d as the dependent variable; the age at which an animal is predicted to reach a predefined live weight was then estimated based on the model regression coefficients. Fixed effects included in the multiple regression model were dam parity, gestation length, and parental average genetic merit for relevant traits available in Ireland; namely, birth weight, birth size, and carcass weight. Herd of origin was included as a random effect, with all calves having been sold directly from the farm of birth. Live weight data were recorded at the point of sale when calves were, on average, 26 d old with a mean live weight of 56.6 kg. Animals were randomly assigned to 10 separate (i.e., folds) cross-validation data sets without replacement (i.e., each fold consisted of a different 10% of the data to test the model, with the remaining 90% of data being used to train the model) to quantify the accuracy of prediction. Across all data, the correlation between actual and predicted live weight was 0.76; the regression coefficient of actual live weight on predicted live weight across all data was 0.99. The root mean squared error of prediction varied from 4.40 to 6.66 kg per fold. Across all data, the root mean squared error was 5.61 kg, implying that 68% of live weight predictions were within 5.61 kg of the actual live weight. Given the potential availability of all model features in advance of birth (gestation length can be predicted from ultrasound examination of the pregnant uterus, although substituting parental average genetic merit for gestation length had minimal effect on model performance), predictions can be integrated into a dairy farm decision support tool to aid in the management of labor and infrastructure resources to achieve minimum live weight specifications before sale.

Commercial beef farms excelling in terminal and maternal genetic merit generate more gross profit

Validation of beef total merit breeding indexes for improving performance and profitability has previously been undertaken at the individual animal level; however, no herd-level validation of beef genetic merit and profit has been previously investigated. The objective of the present study was to quantify the relationship between herd profitability and both herd-average terminal and maternal genetic merit across 1,311 commercial Irish beef herds. Herd-level physical and financial performance data were available from a financial benchmarking tool used by Irish farmers and their extension advisors. Animal genetic merit data originated from the Irish Cattle Breeding Federation who undertake the national beef and dairy genetic evaluations. Herd-average genetic merit variables included the terminal index of young animals, the maternal index of dams, and the terminal index of service sires. The herds represented three production systems: 1) cow-calf to beef, 2) cow-calf to weanling/yearling, and 3) weanling/yearling to beef. Associations between herd financial performance metrics and herd average genetic merit variables were quantified using a series of linear mixed models with year, production system, herd size, stocking rate, concentrate input, and the two-way interactions between production system and herd size, stocking rate, and concentrate input included as nuisance factors. Herd nested within the county of Ireland (n = 26) was included as a repeated effect. Herds with young cattle excelling in terminal index enjoyed greater gross and net profit per hectare (ha), per livestock unit (LU), and per kg net live-weight output. The change in gross profit per LU per unit change in the terminal index of young animals was €1.41 (SE = 0.23), while the respective regression coefficient for net profit per LU was €1.37 (SE = 0.30); the standard deviation of the terminal index is €37. Herd-average dam maternal index and sire terminal index were both independently positively associated with gross profit per ha and gross profit per LU. Each one unit increase in dam maternal index (standard deviation of €38) was associated with a €1.40 (SE = 0.48) and €0.76 (SE = 0.29) greater gross profit per ha and per LU, respectively. Results from the present study at the herd-level concur with previous validation studies at the individual animal level thus instilling further confidence among stakeholders as to the expected improvement in herd profitability with improving genetic merit.